Assessment of computer games

ABSTRACT

A method of improving a computer game, the method including the steps of: (a) causing a player to play the computer game in which various game situations are presented to the player during the course of the game; (b) recording game situation parameters corresponding to the various game situations of step (a); (c) determining brain activity of the player during each of the game situations which are presented to the player; (d) evaluating effectiveness of the game situation parameters by reference to brain activities determined in step (c) for each of the game situation parameters recorded in step (b); and (e) improving the game by eliminating or modifying those game situations which have low levels of brain activity as determined in step (d).

Computer games and computer based entertainment constitute a large and rapidly growing economic sector. The development costs for the more complex internet based multiplayer games are a very significant investment for even the largest game development corporations. At present, the likely commercial success of a computer game is determined by asking people to report their impressions of the game and then make modifications to enhance the playability and enjoyment of the games.

The likely success of any game depends on the extent to which the player is engaged in the game and also the extent to which particular situations elicit the desired emotional state, such as excitement, fear, pleasure etc.

The most important psychological measure is ‘engagement’. The extent to which the game engages the player is given by is given by the weighted mean brain activity during the initial period at prefrontal sites described by the expression below:

Engagement=(b ₁*brain activity at electrode F ₃ +b ₂* brain activity at electrode P _(p1) +b ₃*brain activity advance at electrode F ₄ +b ₄*brain activity at electrode F _(p2))   Equation 1

-   -   where: b1=0.1, b2=0.4, b3=0.1, b4=0.4

If inverse mapping techniques are used, the relevant expression is:

Engagement=(d ₁*brain activity at right orbito frontal cortex (in vicinity of Brodman area 11)+d ₂*brain activity at right dorso-lateral prefrontal cortex (in vicinity of Brodman area 9)+d ₃*brain activity at left orbito frontal cortex (in vicinity of Brodman area 11)+d₄*brain activity at left dorso-lateral prefrontal cortex (in vicinity of Brodman area 9))   Equation 2

-   -   where: d₁=0.1, d₂=0.4, d₃=0.1, d₄=0.4

Other psychological measures and their brain activity indicators that are of relevance include:

Visual attention associated with a given set of situation parameters is indicated by increased brain activity at left and right occipital recording sites. In the International 10-20 system that labels recording sites on the brain, the positions referred to above correspond to the vicinity of O₁ and O₂. If activity in deeper parts of the brain are assessed using inverse mapping techniques such as BESA, EMSE or LORETA in combination with either electrical or magnetic recordings or SSVEP or SSVER, the relevant location in the left cerebral cortex is the vicinity of the left and right occipital lobe.

The Emotional intensity, associated with a set of situation parameters is indicated by increased brain activity at right parieto-temporal region, preferable approximately equidistant from right hemisphere electrodes O₂, P₄ and T₆ during the initial period. If inverse mapping techniques are used, the relevant location in the right cerebral cortex is the vicinity of the right parieto-temporal junction.

The extent to which individuals are attracted or repelled by a game situation associated with a given set of situation parameters is given by the difference between brain activity at left frontal/prefrontal and right frontal/prefrontal regions. Attraction is indicated by a larger activity in the left hemisphere compared to the right while repulsion is indicated by greater activity in the right hemisphere compared to the left.

Attraction=(a ₁*brain activity recorded at electrode F ₃ +a ₂*brain activity recorded at electrode F _(p1) −a ₃*brain activity recorded at electrode F ₄ −a4*brain activity recorded at electrode F _(p2))   Equation 3

-   -   where: a₁=a₂=a₃=a₄=1.0

A positive value for the Attraction measure is associated with the participants finding the material attractive and liked while a negative measure is associated with repulsion or dislike.

If inverse mapping techniques are used, the relevant expression is:

Attraction=(c ₁*brain activity at right orbito−brain activity at frontal cortex (in vicinity of Brodman area 11)+c ₂*brain activity at right dorso-lateral prefrontal cortex (in vicinity of Brodman area 9)+c ₃*brain activity at left orbito frontal cortex (in vicinity of Brodman area 11)+c ₄*brain activity at left dorso-lateral prefrontal cortex (vicinity of Brodman area 9))   Equation 4

-   -   where: c₁=1, c₂=1, c₃=1, c₄=1

Determining Computer Game Situation Parameters

The game situation parameters are a set of digital values that uniquely identify the situation of the game player. These parameters will vary with the nature of the game and will also vary with time as the player progresses through the game. For instance, in a driving simulation game, the game situation parameters would comprise the location of the player's car on the simulated track or landscape, the speed and direction of the players car as well as the state of the steering wheel, brakes and gears. In an adventure game, the game situation parameters may include the location and orientation of the player's representation (avatar) within the simulated environment such as a building, battleground or streetscape. In addition, the game situation parameters could include the status of the avatar such as its capabilities (eg strength, ‘magical powers’ etc) as well as the location and actions of other avatars (in multi player games) or computer generated denizens such as monsters, aliens, wizards. etc. The game situation parameters change with time and a record of each game situation parameter as a function of time can be stored as a numerical array in the game computer memory. While a game is being played, the relevant game situation parameters are held in computer memory and when active playing ceases transferred to hard disk memory or another digital storage medium such as flash memory.

The game software developers would use standard software such as C++ or specialized computer games development software such as DaskBASIC (The Game Creator Ltd, ‘Rockville’, Warrington Rd, Lower Ince, Wigan, Lancashire, WN3 4QG, UK) to incorporate the software to identify and store the game situation parameters while a game is being played.

The object of the present invention is to provide a technique which enables quantitative evaluation of a player's psychological response to various components of a computer game in order to be able to improve the computer game.

According to the present invention there is provided a method of improving a computer game, the method including the steps of:

(a) causing a player to play the computer game in which various game situations are presented to the player during the course of the game;

(b) recording game situation parameters corresponding to the various game situations of step (a);

(c) determining brain activity of the player during each of the game situations which are presented to the player;

(d) evaluating effectiveness of the game situation parameters by reference to brain activities determined in step (c) for each of the game situation parameters recorded in step (b); and

(e) improving the game by eliminating or modifying those game situations which have low levels of brain activity as determined in step (d).

The invention also provides a system for assessing entertainment value of a computer game including:

(a) a computer upon which the computer game to be assessed can be played, the computer being arranged to record game situation parameters corresponding to various game situations which occur during playing of the computer game;

(b) means for determining brain activity of the player during each of the game situations which occur during playing of the computer game; and

(c) means for evaluating the effectiveness of the game situation parameters by reference to brain activities determined by said means for determining brain activity for each of the recorded game situation parameters.

It will be appreciated that the present invention provides a method that relies on measurement of brain activity rather than verbal responses to questionnaires or other voluntary feedback in order to determine an individual player's response to various components of a computer game. Accordingly, the method of the invention enables game developers to improve the likely commercial success of the game by modifying components of the game that are found to be less engaging.

In one embodiment, brain activity is measured while subjects or players take part in the computer game. Simultaneously, the specific situations encountered by the player are also recorded as a stream of digital parameters specifying the player situation or Situation Parameters.

Typically, 20 to 100 players will play the game while brain activity and Situation Parameters are recorded. To determine the brain activity associated with a specific set of situation parameters or a range of situation parameters, individual player brain activity is averaged for all points in time where the recorded situation parameters satisfy certain predetermined criteria. For each individual player, this will yield a set of mean brain activity measures associated with each of the situation parameter criteria. Brain activity for a given situation parameter criterion is then averaged across all the players or subset of players.

Measuring Brain Activity

A number of methods are available for measuring brain activity. The main feature they must possess is adequate temporal resolution or the capacity to track the rapid changes in brain activity. Spontaneous brain electrical activity or the electroencephalogram (EEG) or the brain electrical activity evoked by a continuous visual flicker that is the Steady State Visually Evoked (SSVEP) are two examples of brain electrical activity that can be used to measure changes in brain activity with sufficient temporal resolution. The equivalent spontaneous magnetic brain activity or the magnetoencephalogram (MEG) and the brain magnetic activity evoked by a continuous visual flicker Steady State Visually Evoked Response (SSVER).

The Electroencephalogram and Magnetoencephalogram (EEG and MEG)

The EEG and MEG are the record of spontaneous brain electrical and magnetic activity recorded at or near the scalp surface. Brain activity can be assessed from the following EEG or MEG components.

A number of methods are available for measuring brain activity. The main feature they must possess is adequate temporal resolution or the capacity to track the rapid changes in brain activity. Spontaneous brain electrical activity or the electroencephalogram (EEG) or the brain electrical activity evoked by a continuous visual flicker that is the Steady State Visually Evoked (SSVEP) are two examples of brain electrical activity that can be used to measure changes in brain activity with sufficient temporal resolution. The equivalent spontaneous magnetic brain activity or the magnetoencephalogram (MEG) and the brain magnetic activity evoked by a continuous visual flicker Steady State Visually Evoked Response (SSVER).

1. Gamma or High Frequency EEG or MEG Activity

This is generally defined as EEG or MEG activity comprising frequencies between 35 Hz and 80 Hz. Increased levels of Gamma activity are associated with increased levels of brain activity, especially concerned with perception. (Fitzgibbon S P, Pope K J, Mackenzie L, Clark C R, Willoughby J O. Cognitive tasks augment gamma EEG power. Clin Neurophysiol. 2004: 115:1802-1809.)

If scalp EEG gamma activity is used as the indicator of brain activity, the relevant scalp recording sites are listed above. If EEG gamma activity at the specific brain regions listed above is used as the indicator brain activity then inverse mapping techniques such as LORETA must be used (Pascual-Marqui R, Michel C, Lehmann D (1994): Low resolution electromagnetic tomography: a new method for localizing electrical activity in the brain. Int J Psychophysiol 18:49-65).

If MEG gamma activity at the specific brain regions listed above is used as the indicator of brain activity, then the multi-detector MEG recording system must be used in conjunction with an MEG inverse mapping technique (see Uutela K, Ha{umlaut over ( )}ma{umlaut over ( )}la{umlaut over ( )}inen M, Somersalo E (1999): Visualization of magnetoencephalographic data using minimum current estimates. Neuroimage 10:173-180. and Fuchs M, Wagner M, Kohler T, Wischmann HA (1999): Linear and nonlinear current density reconstructions. J Clin Neurophysiol 16:267-295).

2. Frequency of EEG or MEG Alpha Activity

Brain activity may also be indexed by changes in the frequency of the ongoing EEG or MEG in the alpha frequency range (8.0 Hz-13.0 Hz). Increased frequency is an indication of increased activity. The frequency needs to me estimated with high temporal resolution. Two techniques that can be used to measure ‘instantaneous frequency’ are complex demodulation (Walter D, The method of Complex Demodulation. Electroencephalog. Clin. Neurophysiol. 1968: Suppl 27:53-7) and the use of the Hilbert Transform (Leon Cohen, “Time-frequency analysis”, Prentice-Hall, 1995). Increased brain activity is indicated by an increase in the instantaneous frequency of the EEG in the alpha frequency range.

If the frequency of scalp EEG alpha activity is used as the indicator of brain activity, the relevant scalp recording sites are listed above. If the frequency of EEG alpha activity at the specific brain regions listed above is used as the indicator brain activity then inverse mapping techniques such as LORETA must be used (Pascual-Marqui R, Michel C, Lehmann D (1994): Low resolution electromagnetic tomography: a new method for localizing electrical activity in the brain. Int J Psychophysiol 18:49-65).

If the frequency of MEG alpha activity at the specific brain regions listed above is used as the indicator of brain activity, then the multi-detector MEG recording system must be used in conjunction with an MEG inverse mapping technique (see Uutela K, Ha{umlaut over ( )}ma{umlaut over ( )}la{umlaut over ( )}inen M, Somersalo E (1999): Visualization of magnetoencephalographic data using minimum current estimates. Neuroimage 10:173-180. and Fuchs M, Wagner M, Kohler T, Wischmann HA (1999): Linear and nonlinear current density reconstructions. J Clin Neurophysiol 16:267-295).

3. SSVEP or SSVER Phase as an Indicator of Brain Activity

Brain activity may also be indicated by the phase of the Steady State Visually Evoked Potential (SSVEP) or the Steady State Visually Evoked Response (SSVER).

U.S. Pat. Nos. 4,955,938, 5,331,969 and 6,792,304 (the contents of which are hereby incorporated herein by reference) disclose technique for obtaining a steady state visually evoked potential (SSVEP) from a subject. This technique can also be used to obtain a steady state visually evoked response (SSVER). These patents disclose the use of Fourier analysis in order to rapidly obtain the SSVEP and SSVER phase and changes thereto.

The invention will now be further described with reference to the accompanying drawings, in which:

FIG. 1 is a schematic diagram of a system of the invention;

FIG. 2 is a schematic view showing in more detail the manner in which visual flicker stimuli are presented to a subject; and

FIG. 3 is a graph showing opacity of the screen as a function of radius.

FIG. 1 schematically illustrates a system 50 for determining the response of a subject or a group of subjects to audio-visual material presented on a video screen 3 and loudspeaker 2. The system includes a computer 1 which controls various parts of the hardware and also performs computation on signals derived from the brain activity of the subject 7, as will be described below. The computer 1 also holds the images and sounds which can be presented to one or more subject 7 on the screen 3 and/or through the loudspeaker 2.

The subject or subjects 7 to be tested are fitted with a headset 5 which includes a plurality of electrodes for obtaining brain electrical activity from various sights on the scalp of the subject 7. In the event that the SSVER is used, the recording electrodes in the headset 5 are not used and a commercial MEG recording system such as the CTF MEG System manufactured by VSM MedTech Ltd. of 9 Burbidge Street, Coquitlam, BC, Canada, can be used instead. The headset includes a visor 4 which includes half silvered mirrors 8 and white light Light Emitting Diode (LED) arrays 9, as shown in FIG. 2. The half silvered mirrors are arranged to direct light from the LED arrays 9 towards the eyes of the subject 7. The LED arrays 9 are controlled so that the light intensity there from varies sinusoidally under the control of control circuitry 6. The control circuitry 6 includes a waveform generator for generating the sinusoidal signal. In the event that the SSVER is used, the light from the LED array is conveyed to the visor via a fibre optic system. The circuitry 6 also includes amplifiers, filters, analogue to digital converters and a USB interface or a TCP interface or other digital interface for coupling the various electrode signals into the computer 1.

A translucent screen 10 is located in front of each LED array 9. Printed on the screen is an opaque pattern. The opacity is a maximum in a circular area in the centre of the center of the screen. Beyond the circular area, the opacity falls off smoothly with radial distance from the circular area circumference, preferably, the opacity should fall off as a Gaussian function described by Equation 5 below. The screen reduces the flicker in the central visual field thus giving subjects a clear view of the visually presented material. The size of the central opaque circle should be such as to occlude the visual flicker in the central visual field between 1-4 degrees vertically and horizontally.

-   -   If r<R then P=1     -   If r≧R then P is given by the equation 1 below.

P=e^(−(r−R) ² ^(/G) ²   Equation 5

-   -   where P is the opacity of the pattern on the translucent screen.         An opacity of P=1.0 corresponds to no light being transmitted         through the screen while an opacity of P=0 corresponds to         complete transparency.

R is the radius of the central opaque disk while r is the radial distance from the centre of the opaque disk. G is a parameter that determines the rate of fall-off of opacity with radial distance. Typically G has values between R/4 and 2R. FIG. 3 illustrates the fall-off of opacity with radial distance from the centre of the disk. In FIG. 3, R=1 and G=2R.

The computer 1 includes software which calculates SSVEP or SSVER amplitude and phase from each of the electrodes in the headset 5 or MEG sensors.

Details of the hardware and software required for generating SSVEP and SSVER are well known and need not be described in detail. In this respect reference is made to the aforementioned United States patent specifications which disclose details of the hardware and techniques for computation of SSVEP. Briefly, the subject 7 views the video screen 3 through the special visor 4 which delivers a continuous background flicker to the peripheral vision. The frequency of the background flicker is typically 13 Hz but may be selected to be between 3 Hz and 50 Hz. More than one flicker frequency can be presented simultaneously. The number of frequencies can vary between 1 and 5. Brain electrical activity will be recorded using specialized electronic hardware that filters and amplifies the signal, digitizes it in the circuit 6 where it is then transferred to the computer 1 for storage and analysis.

When using the SSVEP, brain electrical activity is recorded using multiple electrodes in headset 5 or another commercially available multi-electrode system such as Electro-cap (ECI Inc., Eaton, Ohio USA). When using the SSVER, commercial MEG recording system such as the CTF MEG System manufactured by VSM MedTech Ltd may be used. The number of electrodes or magnetic recording sites is normally not less than 8 and normally not more than 128, typically 16 to 32.

Brain electrical activity at each of the electrodes is conducted to a signal conditioning system and control circuitry 6. The circuitry 6 includes multistage fixed gain amplification, band pass filtering and sample-and-hold circuitry for each channel. Amplified/filtered brain activity is digitized to 16-24 bit accuracy at a rate not less than 300 Hz and transferred to the computer 1 for storage on hard disk. The timing of each brain electrical sample together with the time of presentation of different components of the audio-visual material are also registered and stored to an accuracy 10 microseconds. The equivalent MEG recording system that is commercially available performs the same functions.

SSVEP and SSVER Amplitude and Phase

The digitized brain electrical activity (electroencephalogram or EEG) brain magnetic activity (MEG) together with timing of the stimulus zero crossings enables one to calculate the SSVEP or SSVER elicited by the flicker at a particular stimulus frequency from the recorded EEG or MEG or from EEG or MEG data that has been pre-processed using Independent Components Analysis (ICA) to remove artefacts and increase the signal to noise ratio. [Bell A. J. and Sejnowski T. J. 1995. An information maximisation approach to blind separation and blind deconvolution, Neural Computation, 7, 6, 1129-1159; T-P. Jung, S. Makeig, M. Westerfield, J. Townsend, E. Courchesne and T. J. Sejnowskik, Independent component analysis of single-trial event-related potential Human Brain Mapping, 14(3):168-85, 2001.]

Calculation of SSVEP or SSVER amplitude and phase for each stimulus cycle for a given stimulus frequency. Calculation accomplished used Fourier techniques using Equations 6 and 7 below.

$\begin{matrix} {{a_{n} = {\frac{1}{S\; \Delta \; \tau}{\sum\limits_{i = 0}^{S - 1}\; {{f\left( {{nT} + {i\; \Delta \; \tau}} \right)}{\cos \left( {\frac{2\; \pi}{T}\left( {{nT} + {i\; \Delta \; \tau}} \right)} \right)}}}}}{b_{n} = {\frac{1}{S\; \Delta \; \tau}{\sum\limits_{i = 0}^{S - 1}\; {{f\left( {{nT} + {i\; \Delta \; \tau}} \right)}{\sin \left( {\frac{2\; \pi}{T}\left( {{nT} + {i\mspace{11mu} \Delta \; \tau}} \right)} \right)}}}}}} & {{Equation}\mspace{14mu} 6} \end{matrix}$

Calculation of SSVEP Fourier components where a_(n) and b_(n) are the cosine and sine Fourier coefficients respectively. n represents the nth stimulus cycle, S is the number of samples per stimulus cycle (typically 16 samples per cycle), Δτ is the time interval between samples, T is the period of one cycle and f(nT+iΔτ) is the EEG or MEG signal (raw or pre-processed using ICA).

$\begin{matrix} {{{SSVEP}_{amplitude} = {\sqrt{\left( {A_{n}^{2} + B_{n}^{2}} \right)}\mspace{14mu} {or}}}{{SSVER}_{amplitude} = \sqrt{\left( {A_{n}^{2} + B_{n}^{2}} \right)}}{{SSVEP}_{phase} = {a\; {\tan \left( \frac{B_{n}}{A_{n}} \right)}\mspace{14mu} {or}}}\text{}{{SSVER}_{phase} = {a\; {\tan \left( \frac{B_{n}}{A_{n}} \right)}}}} & {{Equation}\mspace{14mu} 7} \end{matrix}$

Where A_(n) and B_(n) are overlapping smoothed Fourier coefficients calculated by using Equation 4 below.

$\begin{matrix} {{A_{n} = {\sum\limits_{i = 1}^{i = N}\; {a_{n + i}/N}}}{B_{n} = {\sum\limits_{i = 1}^{i = N}\; {b_{n + i}/N}}}} & {{Equation}\mspace{14mu} 8} \end{matrix}$

Amplitude and phase components can be calculated using either single cycle Fourier coefficients (a_(n) and b_(n)) or coefficients that have been calculated by smoothing across multiple cycles (A_(n) and B_(n)).

Equations 7 and 8 describe the procedure for calculating the smoothed SSVEP or SSVER coefficients for a single subject. For pooled data, the SSVEP or SSVER coefficients (A_(n) and B_(n)) for a given electrode are averaged (or pooled) across all of the subjects or a selected group of subjects.

As the number of cycles used in the smoothing increases, the signal to noise ratio increases while the temporal resolution decreases. The number of cycles used in the smoothing is typically in excess of 5 and less than 130.

The above equations apply to scalp SSVEP data as well as brain electrical activity inferred at the cortical surface adjacent to the skull and deeper regions. Activity in deeper regions of the brain such as the orbito-frontal cortex or ventro-medial cortex can be determined using a number of available inverse mapping techniques such as EMSE (Source Signal Imaging, Inc, 2323 Broadway, Suite 102, San Diego, Calif. 92102, USA) and LORETA (Pascual-Marqui R, Michel C, Lehmann D (1994): Low resolution electromagnetic tomography: a new method for localizing electrical activity in the brain. Int J Psychophysiol 18:49-65). If the SSVER amplitude or phase changes at the specific brain regions listed above are used as the indicator of brain activity, then the multi-detector MEG recording system must be used in conjunction with an MEG inverse mapping technique (see Uutela K, Ha{umlaut over ( )}ma{umlaut over ( )}la{umlaut over ( )}inen M, Somersalo E (1999): Visualization of magnetoencephalographic data using minimum current estimates. Neuroimage 10:173-180. and Fuchs M, Wagner M, Kohler T, Wischmann H A (1999): Linear and nonlinear current density reconstructions. J Clin Neurophysiol 16:267-295).

While participants are playing the computer game, the visual flicker is switched on in the visor 8 and brain electrical activity is recorded continuously on the computer 1. At the end of the recording stage, the SSVEP or SSVER amplitude and phase are separately calculated for each individual.

EXAMPLE

In the following example, a computer game development company needs to assess the psychological impact of a computer game under development. 20 to 100 participants drawn from the target market for the game are recruited into the study. Brain activity is then recorded while the participants play the computer under development. Each participant plays the game on an individual computer located in a booth to reduce distraction. To record brain activity, the headsets 5 are placed on their heads and the visors 4 are placed in position and adjusted so that for each participant the foveal block by the screens 10 prevents the appearance of the flicker over the central portion of the screen 3.

Once brain activity and situation parameters have been recorded for all game playing participants, each participants brain activity is averaged when the situation parameters satisfy certain criteria. As an example, one such criterion could be a specific geographical location and speed prior to a collision in a racing car game. Alternatively, in a war game, it could be a particular battlefield location when the player is under attack from more than three enemy soldiers. Each game would therefore have a unique set of situation parameters criteria that reflected the components of the game where the game developer required player psychological information. Brain activity measured for the various situation parameters criteria can then be averaged across all the players to obtain a representative response for each criterion or set of specified situation parameters.

While the most important psychological parameters are engagement and attention, other parameters may also be important at various portions of the game. For example, emotional intensity may be important in certain components of the game while long-term memory may be important where information needs to be remembered or where advertising takes place in the game. The psychological parameters can be measured using the techniques described earlier and these can be plotted graphically for the various game situation parameters of interest. The game developer can then determine which of the game parameters has a relatively low entertainment value. These parts of the game could therefore be eliminated or modified to make them more interesting so as to achieve higher measures of engagement and attention or other psychological responses of interest.

The accuracy of the assessment can be improved by measuring the brain activity of the players against reference levels. One convenient way to do this would be to average the brain activity for each player during the whole game and then compare the brain activity during the game situations of interest to the average game level. This provides a more accurate measure of the players' psychological responses to the game situations of interest. Alternatively, prior to commencement of a game, each of the players could be presented with a series of still images or the like together with musical accompaniment and brain activities measured in the usual way during this reference period. Brain activities can then be assessed against the reference levels which also provides increased accuracy. Reference periods presented in this way also provide an opportunity for comparisons to be made between game situations of different games rather than game situations within a single game.

Many modifications will be apparent to those skilled in the art without departing from the spirit and scope of the invention. 

1. A method of improving a computer game, the method including the steps of: (a) causing a player to play the computer game in which various game situations are presented to the player during the course of the game; (b) recording game situation parameters corresponding to the various game situations of step (a); (c) determining brain activity of the player during each of the game situations which are presented to the player; (d) evaluating effectiveness of the game situation parameters by reference to brain activities determined in step (c) for each of the game situation parameters recorded in step (b); and (e) improving the game by eliminating or modifying those game situations which have low levels of brain activity as determined in step (d).
 2. A method as claimed in claim 1 wherein the brain activities determined in step (c) are averaged for each game situation parameter.
 3. A method as claimed in claim 1 or 2 wherein step (a) is performed by a plurality of players and step (c) includes the steps of averaging the brain activities of the players.
 4. A method as claimed in claim 3 wherein step (c) is carried out by determining gamma or high frequency EEG or MEG activity.
 5. A method as claimed in claim 3 wherein step (c) is carried out by detecting EEG or MEG activity in the frequency range 8 to 13 Hz.
 6. A method as claimed in claim 3 wherein step (c) is carried out by assessment of the phase of steady state visually evoked potentials (SSVEP) in EEG signals obtained from the players or by assessment of steady state visually evoked responses (SSVER) in MEG signals obtained from the players.
 7. A method as claimed in any one of claims 1 to 6 wherein step (c) includes the steps of placing electrodes at scalp sites to obtain output EEG signals which enable assessment of: engagement with the game situations; attraction associated with the game situations; emotional intensity associated with the game situations; and/or long term memory encoding associated with the game situations.
 8. A method as claimed in claim 7 including the step of applying a sinusoidally varying visual flicker stimulus to each player during step (c) to thereby enable calculation of Fourier coefficients from said output signals to thereby enable calculation of said SSVEP amplitudes and/or phase differences.
 9. A method as claimed in claim 8 wherein said SSVEP amplitude and phase are calculated by the equations: ${{SSVEP}_{amplitude} = \sqrt{\left( {A_{n}^{2} + B_{n}^{2}} \right)}}\mspace{14mu}$ ${{SSVEP}_{phase} = {a\; {\tan \left( \frac{B_{n}}{A_{n}} \right)}}}\mspace{14mu}$ where: a_(n) and b_(n) are cosine and sine Fourier coefficients calculated by the equations: $a_{n} = {\frac{1}{S\; \Delta \; \tau}{\sum\limits_{i = 0}^{S - 1}\; {{f\left( {{nT} + {i\; \Delta \; \tau}} \right)}{\cos \left( {\frac{2\; \pi}{T}\left( {{nT} + {i\; \Delta \; \tau}} \right)} \right)}}}}$ $b_{n} = {\frac{1}{S\; \Delta \; \tau}{\sum\limits_{i = 0}^{S - 1}\; {{f\left( {{nT} + {i\; \Delta \; \tau}} \right)}{\sin \left( {\frac{2\; \pi}{T}\left( {{nT} + {i\mspace{11mu} \Delta \; \tau}} \right)} \right)}}}}$ where: a_(n) and b_(n) are the cosine and sine Fourier coefficients respectively where; n represents the nth flicker stimulus cycle; S is the number of samples per flicker stimulus cycle; Δτ is the time interval between samples; T is the period of one cycle; f(nT+iΔr) is the EEG signal (raw or pre-processed using ICA) obtained from said predetermined scalp sites; and wherein A_(n) and B_(n) are overlapping smoothed Fourier coefficients calculated by using the equation: $A_{n} = {\sum\limits_{i = 1}^{i = N}\; {a_{n + i}/N}}$ $B_{n} = {\sum\limits_{i = 1}^{i = N}\; {b_{n + i}/N}}$
 10. A method as claimed in claim 9 including the steps of: obtaining EEG signals from a plurality of scalp sites of each player; and utilising inverse mapping techniques such as BESA, EMSA or LORETA to produce modified EEG signals which represent activity in deeper regions of the brain of each subject such as the orbito-frontal cortex or the ventro-medial cortex.
 11. A method as claimed in claim 9 or 10 including the step of averaging the Fourier coefficients A_(n) and B_(n) for a selected group of players and then calculating the SSVEP amplitudes and SSVEP phase differences for said group of players.
 12. A method as claimed in any one of claims 8 to 11 wherein the flicker signal is applied only to the peripheral vision of each player.
 13. A method as claimed in claim 12 including the steps of directing the flicker signal towards the eyes of each player via first and second screens and wherein each screen includes an opaque area, and wherein the method further includes the step of positioning the screens to the relative position of each player such that said opaque areas prevent said flicker signal impinging on the fovea of each eye of each player.
 14. A method as claimed in claim 13 wherein the opacity of each screen decreases as a function of distance from its opaque area so that the intensity of the flicker signal impinging on each retina of each player decreases in value from the central vision to the peripheral vision.
 15. A method as claimed in claim 14 including the step of applying a masking pattern to each screen to define the opacity thereof, the method including the step of applying the pattern in accordance with a masking pattern function which provides zero or low gradients for changes in opacity adjacent to its opaque area and peripheral areas thereof which define parts of the flicker signal impinging on the peripheral vision of each player.
 16. A method as claimed in claim 15 wherein the opaque area of each screen is circular and wherein the masking pattern function is selected to be a Gaussian function, so that the opacity P of the screen is defined by the equation: P=e^(−(r−R)) ² ^(/G) ² where: r is the radial distance from the centre of the opaque area; and G is a parameter that determines the rate of fall-off of opacity with radial distance, and wherein when r<R, P=1.
 17. A method as claimed in claim 16 wherein G has a value in the range R/4 and 2R.
 18. A method as claimed in claim 9 including the step of applying an electrode to the scalp of each player at a site which is approximately equidistant from sites O₂, P₄ and T₆, calculating SSVEP amplitudes and phase differences from EEG signals from said electrode whereby the output signals indicate each player's emotional intensity associated with the game situations or game situation parameters.
 19. A method as claimed in claim 10 wherein the step of utilising inverse mapping determines brain activity in the right cerebral cortex in the vicinity of the right parieto-temporal junction whereby the output signals indicate each player's emotional intensity associated with the game situations or game situation parameters.
 20. A method as claimed in claim 9 including the steps of applying an electrode to the scalp of each player at the F₃, F₄, F_(p1) and F_(p2) sites, calculating SSVEP amplitudes and phase differences from EEG signals from said electrodes, calculating values for attraction-repulsion using the equation: attraction=(a ₁*SSVEP phase advance at electrode F ₃ +a ₂*SSVEP phase advance at electrode F _(p1) −a ₃*SSVEP phase advance at electrode F ₄ −a ₄*SSVEP phase advance at electrode F _(p2)) where a₁=a₂=a₃=a₄=1.0 whereby said values indicate each player's attraction or repulsion towards the game situations or game situation parameters.
 21. A method as claimed in claim 10 wherein the step of utilising inverse mapping determines brain activity in: the right orbito-frontal cortex in the vicinity of Brodman area 11; the right dorso-lateral prefrontal cortex in the vicinity of Brodman area 9; the left orbito frontal cortex in the vicinity of Brodman area 11; and the left dorso-lateral prefrontal cortex in the vicinity of Brodman area 9; and calculating a value for attraction-repulsion using the equation: attraction=(c ₁*right orbito-frontal cortex (in vicinity of Brodman area 11)+c ₂*right dorso-lateral prefrontal cortex (in vicinity of Brodman area 9)+c ₃*left orbito frontal cortex (in vicinity of Brodman area 11)+c ₄*left dorso-lateral prefrontal cortex (vicinity of Brodman area 9)) where c₁=1, c₂=1, c₃=1, c₄=1, whereby said values indicate each player's attraction or repulsion towards the game situations or game situation parameters.
 22. A method as claimed in claim 9 including the steps of applying electrodes to the scalp of each player at F₃, F₄, P_(p1) and F_(p2) sites, calculating SSVEP amplitudes and phase differences from said electrodes, calculating values for engagement in features of the advertisement by a weighted mean SSVEP phase advance at said sites using the equation: engagement=(b ₁*SSVEP phase advance at electrode F ₃ +b ₂*SSVEP phase advance at electrode P _(p1) +b ₃*SSVEP phase advance at electrode F ₄ +b ₄*SSVEP phase advance at Electrode F _(p2)) where b₁=0.1, b₂=0.4, b₃=0.1, b₄=0.4, whereby said values indicate each player's engagement in the game situations or game situation parameters.
 23. A method as claimed in claim 10 wherein the step of utilising inverse mapping determines brain activity in: the right orbito frontal cortex in the vicinity of Brodman area 11; the right dorso-lateral prefrontal cortex in the vicinity of Brodman area 9; the left frontal cortex in the vicinity of Brodman area 11; and the left dorso-lateral prefrontal cortex in the vicinity of Brodman area 9, calculating SSVEP amplitudes and phase differences from said modified EEG signals from said electrodes; and calculating a value for engagement using the equation: engagement=(d ₁*right orbito frontal cortex (in vicinity of Brodman area 11)+d ₂*right dorso-lateral prefrontal cortex (in vicinity of Brodman area 9)+d ₃*left orbito frontal cortex (in vicinity of Brodman area 11)+d ₄*left dorso-lateral prefrontal cortex (in vicinity of Brodman area 9)) where d₁=0.1, d₂=0.4, d₃=0.1, d₄=0.4, whereby said values indicate each player's engagement in the game situations or game situation parameters.
 24. A system for assessing entertainment value of a computer game including: (a) a computer upon which the computer game to be assessed can be played, the computer being arranged to record game situation parameters corresponding to various game situations which occur during playing of the computer game; (b) means for determining brain activity of the player during each of the game situations which occur during playing of the computer game; and (c) means for evaluating the effectiveness of the game situation parameters by reference to brain activities determined by said means for determining brain activity for each of the recorded game situation parameters. 